Economics Commons^™

Enhanced Prediction Of Stock Markets Using A Novel Deep Learning Model Plstm-Tal In Urbanized Smart Cities, Saima Latif, Nadeem Javaid, Faheem Aslam, Abdulaziz Aldegheishem, Nabil Alrajeh, Safdar Hussain Bouk

School of Cybersecurity Faculty Publications

Accurate predictions of stock markets are important for investors and other stakeholders of the equity markets to formulate profitable investment strategies. The improved accuracy of a prediction model even with a slight margin can translate into considerable monetary returns. However, the stock markets' prediction is regarded as an intricate research problem for the noise, complexity and volatility of the stocks' data. In recent years, the deep learning models have been successful in providing robust forecasts for sequential data. We propose a novel deep learning-based hybrid classification model by combining peephole LSTM with temporal attention layer (TAL) to accurately predict the …